1.访问集成文档 http://ai.baidu.com/docs#/FaceSDK-Collect-WithLiveness-Android/top 申请license，下载自动授权的sdk

2. 添加license

3.添加sdk文件

4.修改config文件

package com.baidu.aip.fl;

public class Config {

// 为了apiKey,secretKey为您调用百度人脸在线接口的，如注册，识别等。

// 为了的安全，建议放在您的服务端，端把人脸传给服务器，在服务端端进行人脸注册、识别放在示例里面是为了您快速看到效果

public static String apiKey = "WGV*************m5m";

public static String secretKey = "a4cK**********cs";

public static String licenseID = "bp-*********-android";

public static String licenseFileName = "idl********android";

/**

* groupId，标识一组用户(由数字、字母、下划线组成)，长度限制128B，可以自行定义，只要注册和识别都是同一个组。

* 详情见 http://ai.baidu.com/docs#/Face-API/top

*

* 人脸识别 接口 https://aip.baidubce.com/rest/2.0/face/v2/identify

* 人脸注册 接口 https://aip.baidubce.com/rest/2.0/face/v2/faceset/user/add

*/

public static String groupID = "*******";

}

5.添加类和权限

6.在继承Application类里添加

FaceSDKManager.getInstance().initialize(this, Config.licenseID, Config.licenseFileName);

FaceConfig config = FaceSDKManager.getInstance().getFaceConfig();

// SDK初始化已经设置完默认参数(推荐参数)，您也根据实际需求进行数值调整

// 设置活体动作，通过设置list LivenessTypeEnum.Eye，LivenessTypeEnum.Mouth，LivenessTypeEnum.HeadUp，

// LivenessTypeEnum.HeadDown，LivenessTypeEnum.HeadLeft, LivenessTypeEnum.HeadRight,

// LivenessTypeEnum.HeadLeftOrRight

ListlivenessList = new ArrayList<>();

livenessList.add(LivenessTypeEnum.Mouth);

livenessList.add(LivenessTypeEnum.Eye);

livenessList.add(LivenessTypeEnum.HeadUp);

livenessList.add(LivenessTypeEnum.HeadDown);

livenessList.add(LivenessTypeEnum.HeadLeft);

livenessList.add(LivenessTypeEnum.HeadRight);

config.setLivenessTypeList(livenessList);

// 设置 活体动作是否随机 boolean

config.setLivenessRandom(true);

config.setLivenessRandomCount(2);

// 模糊度范围 (0-1) 推荐小于0.7

config.setBlurnessValue(VALUE_BLURNESS);

// 光照范围 (0-1) 推荐大于40

config.setBrightnessValue(VALUE_BRIGHTNESS);

// 裁剪人脸大小

config.setCropFaceValue(VALUE_CROP_FACE_SIZE);

// 人脸yaw,pitch,row 角度，范围(-45，45)，推荐-15-15

config.setHeadPitchValue(VALUE_HEAD_PITCH);

config.setHeadRollValue(VALUE_HEAD_ROLL);

config.setHeadYawValue(VALUE_HEAD_YAW);

// 最小检测人脸(在图片人脸能够被检测到最小值)80-200， 越小越耗性能，推荐120-200

config.setMinFaceSize(VALUE_MIN_FACE_SIZE);

// 人脸置信度(0-1)推荐大于0.6

config.setNotFaceValue(VALUE_NOT_FACE_THRESHOLD);

// 人脸遮挡范围 (0-1) 推荐小于0.5

config.setOcclusionValue(VALUE_OCCLUSION);

// 是否进行质量检测

// config.setCheckFaceQuality(true);

config.setCheckFaceQuality(false);

// 人脸检测使用线程数

config.setFaceDecodeNumberOfThreads(2);

// 是否开启提示音

config.setSound(true);

FaceSDKManager.getInstance().setFaceConfig(config);

APIService.getInstance().init(this);

APIService.getInstance().setGroupId(Config.groupID);

// 用ak，sk获取token, 调用在线api，如：注册、识别等。为了ak、sk安全，建议放您的服务器，

APIService.getInstance().initAccessTokenWithAkSk(new OnResultListener() {

@Override

public void onResult(AccessToken result) {

Log.i("wtf", "AccessToken->" + result.getAccessToken());

/* handler.post(new Runnable() {

@Override

public void run() {

Toast.makeText(Myapplicaition.this, "启动成功", Toast.LENGTH_LONG).show();

}

});*/

}

@Override

public void onError(FaceError error) {

Log.e("xx", "AccessTokenError:" + error);

error.printStackTrace();

}

}, this, Config.apiKey, Config.secretKey);

//sdk里人脸检测类

public class FaceDetectActivity extends Activity {

//识别出结果的方法

faceDetectManager.setOnFaceDetectListener(new FaceDetectManager.OnFaceDetectListener() {

@Override

public void onDetectFace(final int retCode, FaceInfo[] infos, ImageFrame frame) {

Log.d("retCoderetCode","retCode=="+retCode);

// Log.d("DetectLoginActivity", "retCode is:" + retCode);

String str = "";

if (retCode == 0) {

if (infos != null && infos[0] != null) {

FaceInfo info = infos[0];

boolean distance = false;

if (info != null && frame != null) {

if (info.mWidth >= (0.9 * frame.getWidth())) {

distance = false;

str = getResources().getString(R.string.detect_zoom_out);

} else if (info.mWidth <= 0.4 * frame.getWidth()) {

distance = false;

str = getResources().getString(R.string.detect_zoom_in);

} else {

distance = true;

}

}

boolean headUpDown;

if (info != null) {

if (info.headPose[0] >= ANGLE) {

headUpDown = false;

str = getResources().getString(R.string.detect_head_up);

} else if (info.headPose[0] <= -ANGLE) {

headUpDown = false;

str = getResources().getString(R.string.detect_head_down);

} else {

headUpDown = true;

}

boolean headLeftRight;

if (info.headPose[1] >= ANGLE) {

headLeftRight = false;

str = getResources().getString(R.string.detect_head_left);

} else if (info.headPose[1] <= -ANGLE) {

headLeftRight = false;

str = getResources().getString(R.string.detect_head_right);

} else {

headLeftRight = true;

}

if (distance && headUpDown && headLeftRight) {

mGoodDetect = true;

} else {

mGoodDetect = false;

}

}

}

}

//保存图片到本地

faceDetectManager.setOnTrackListener(new FaceFilter.OnTrackListener() {

@Override

public void onTrack(FaceFilter.TrackedModel trackedModel) {

if (trackedModel.meetCriteria() && mGoodDetect) {

// upload(trackedModel);

mGoodDetect = false;

saveFaceBmp(trackedModel);

}

}

});